Playlists by Year: A Tape Side's Worth of 1982

Hey, it's the greatest songs and instrumental tracks visiting us from the year 1982!


Playlists by Year: A Tape Side's Worth of 2017

The best songs and greatest tracks of 2017.


Playlists by Year: A Tape Side's Worth of 1981

The best songs and greatest tracks from 1981. Lots of mainstream appeal this time round.



Playlists by Year: A Tape Side's Worth of 1979

Listen to punk slowly fading away on the Spotify playlist below.


Playlists by Year: A Tape Side's Worth of 1978

The Spotify Playlist with arguably the best songs from 1978


Playlists by Year: A Tape Side's Worth of 1977

The greatest songs of 1977. Featuring a surprisingly small proportion of punk songs.



Playlists by Year: A Tape Side's Worth of 1975

We've arrived in the mid-70s. Meager times. Nonetheless, here's some of the greatest music from 1975.


Playlists by Year: A Tape Side's Worth of 1970

The Spotify playlist with the greatest songs and instrumentals for the first year after the Gilded Second Half of the Sixties. A pretty good year.


Playlists by Year: A Tape Side's Worth of 1969

The Spotify playlists for one of pop's best years. The Abbey Road medley is one song, obviously.


Playlists by Year: A Tape Side's Worth of 1968

Some 43 minutes from one of the best years in music history.


Playlists by Year: A Tape Side's Worth of 1967

Perhaps the greatest French song ever, plus 11 more tracks of similar quality.


Playlists by Year: A Tape Side's Worth of 1966

The greatest songs of 1966, one of the best years in the history of pop.


Getting ahead in the Lucrative Field of Data Massaging

Evan Warfel has an excellent comment on a post of Andrew Gelman's. Reproduced in full:
Perhaps we are teaching statistics backwards. Instead of teaching students to try and come up with the correct result, we could teach what it feels like to rationalize one’s way through to non-objectivity.

A final exam question might go: This dataset consists of 5 completely uncorrelated variables — I’ve labeled the columns as ‘weight of cat’, ‘probability of attrition’, ‘color of cat [in RGB]’, ‘current age of subject’ and ‘SAT verbal score’. Find a way to make 3 statistically significant correlations and one non-significant correlation. You get an extra point for each spurious t-test you can come up with. The catch is that your entire analysis has to form part of a coherent story. Bonus points go to the 5 most concise answers.


Predictions Concerning Migration to Germany

1. The current love-fest, remindful of the opening of the Berlin Wall, will soon end and something in the range between disillusionment and xenophobia will set in. Like the post-reunification hangover, really, only on steroids, coke and speed.

2. Family reunification legislation (Familienzusammenf├╝hrung) will be severely tightened within the next three years.


Playlists by Year: A Tape Side's Worth of 1961

The greatest songs (and non-song tracks) from 1961, as far as I can tell.


Robin Hanson's Final Words on Signaling

"Falsifiability is just not a very useful concept in social science. Really."

A Two-Step Model of Class-typical Behaviour

Let's start with the example: In the U.S., high-SES people used to smoke more than low-SES people until about 1965. Then the lines crossed, once, and they never crossed again. These days, there are many high-SES people that you don't have to tell about health risks: to them, smoking is prole. And who wants to be prole?

More generally, there are many behaviours that low-SES people show more frequently than low-SES people, and vice-versa. Why? Let me propose a two-step model. First, there is some initial reason why a certain behaviour is shown more often by low-SES people. Then, the behaviour becomes associated with being low SES. Then, the behaviour is reduced even more by high-SES people. 

Smoking is, I think, a good example. Initially, high-SES people may have had access to better information, or have been better at processing the information, or had more self-control, or have put a higher value on health, or what have you, or all of the above. This created an initial smoking gap. This helped associate smoking with being prole. This, in turn, caused people who don't want to be seen as prole to smoke less.

In some cases, the reason for the initial reason could simply be chance.

The model implies that SES differences in smoking were easier to explain in terms of the psychological factors mentioned above (more self-control, etc.) in 1970 than today. Generalizing this is left as an exercise to the reader.


How to Keep Your Man Happy

1. Have sex with him when he wants to.

2. Don't question his respectability.

It seems to me these are the two rules that are true for almost every man, and at the same time are specific to keeping your man happy, rather than keeping your spouse happy.


Negative Externalities

It is not from the benevolence of the butcher, the brewer, or the baker that we expect our dinner, but from their regard to their own interest.
Adam Smith, The Wealth of Nations

Overjoyed, yet slightly appalled that Richard would even think of, let alone do, such a thing, the man gave him ten thousand dollars for the contract, and a second ten thousand dollars for the incredible suffering the mark had experienced.

"You did a good job," he said. Richard liked to please his customers; that was how his business had grown over the years.
 Philip Carlo, The Ice Man: Confessions of a Mafia Contract Killer


Yeah, sort of.

(It worked on reload.)

Economics, Sociology, Extrinsic and Intrinsic Motivation, and Variance, or, Advice for the Tribal Social Scientist

Someone whose name I've forgotten said that economics is all about how people act rationally and sociology is all about how they don't. That's catchy, but not very helful, because it makes you think about the exact meaning of the term "rational", and before you know it, you're writing a book. Let me propose instead (and of course I'm using the broad brush here) that economics is how people are driven by extrinsic motivation and sociology is about how they're driven by intrinsic motivation.

Of course, people are driven by both, so a good social scientist should consider both. But there's more to be said about the two. Extrinsic and intrinsic motivation are functional equivalents, and the less variance there is in one of the two, the more variance in your dependent variable the other is going to explain.

That's a little abstract, so here's an example. For the purposes of the example, please accept the simplification that the two types of motivation are completely independent of each other.

Consider a company unit in which variance in intrinsic work motivation is low, and the mean is also low - that is, everybody's a lazy bastard. Then variance in extrinsic motivation will explain a lot of variance in behaviour. That is, those who have a higher incentive, such as financial rewards, to work, will work harder, while those that have little incentive will work little (high variance, middling mean).

Now consider a company unit in which variance in intrinsic work motivation is low, and the mean is high. Here, everyone will work hard (low variance, high mean), and differences in incentives will have little effect.

Next, start by thinking about extrinsic motivation. If extrinsic motivation's variance is low with a low mean (everyone gets minimum wage, regardless), then how hard people work will be driven by their intrinsic motivation (high variance, middling mean).

Finally, if extrinsic motivation's variance is low with a high mean, everyone will try hard (low variance, high mean).

What does that leave us with? First, if variance in one independent variable is lower, then variance in the other dependent variable will explain more of the variance in the dependent variable. Admittedly, that's a mathematical necessity, and not a new insight. More specifically, it means that economists who want to stick it to the guys in the other building had better select topics where variance in people's intrinsic motivation is low, while sociologists who want to teach those arrogant dicks in the Adam Smith building a lesson should select reasearch areas in which variance in people's extrinsic motivation is low.

And if you own a company, you ought to put a lot of time into selecting people with high intrinsic work motivation, and also think hard about how to taylor rewards to employees' behaviour. You'll want to do both, because you'll be perfect at neither.


Playlists by Year: A Tape Side's Worth of 1958

The greatest songs and other tracks, according to me, from 1958:

Virtual Reality, or, What's So Great about Knausgaard?

I've only read the first two volumes so far, but here's the best answer I've yet seen to the question Why is Knausgaard so great - when really, with all the detail and mundane plotlines, he should be boring:
The answer lies not in Knausgaard’s depth of revelation so much as the intensity of focus he brings to the subject of his life. He seems to punch a hole in the wall between the writer and reader, breaking through to a form of micro-realism and emotional authenticity that makes other novels seem contrived, “made up”, irrelevant. As [Zadie] Smith put it: “You live his life with him. You don’t simply ‘identify’ with the character, effectively you ‘become’ them.”
There's so much talk about literature's ability to put the reader in someone else's head - this is often portrayed as the feature that most differentiates writing from other forms of art, and Steven Pinker even singled out the increase in putting-yourself-in-other-people's-heads caused by the invention of the printing press as the trigger that started the long-term decline in violence ca. 1500-2000. I've read a fair bit of fiction and some memoirs, but have never seen anyone doing it like Knausgaard does.


Genetics, Human Capital, and the Thomas Theorem

In this short presentation on "Genetics and Society" (video), Gregory Cochran points out an obvious incompatability between human capital theory and empirical findings in behaviour genetics: Human capital theory proceeds as though differences in human capital were solely the product of environmental influences, and especially decisions made by parents, but this is known to be false. Cochran goes on to say this has an impact on a point made in human capital theory concerning the quality-quantity tradeoff: The standard view is that you can have many kids and low investment per kid, leading to relatively low human capital in each kid, or you can have many kids, invest heavily in them, and expect them to exhibit high human capital. To the extent that human capital is influenced by genetics, and to the extent that it is not influenced by parents, this tradeoff does not exist. For example, IQ shows practically no response to differences in parental behaviour, hence your kids' expected IQ is independent from your investments, hence independent from the number of kids you have.

But that's a normative point. Empirically, how much people plan to invest in their kids and how many kids they hence choose to have, should be influenced not by the truth itself, but by what people believe to be true. Belief in genetic influences on people's characteristics decreased ca. 1920-1950 and is now low. While research results from the 1970s onwards have shown the popular view to be wrong, these results are not widely known and believed. Hence, decreases in the number of kids people have might still in part be explained by the above-mentioned aspect of human capital theory, if it is combined with the Thomas theorem: "If men define situations as real, they are real in their consequences."


The Greatest Tracks 2010-2014, Part 3

And, finally, the cream of the crop.